Screwing process analysis using multivariate statistical process control

اسناد مشابه

• Multivariate Statistical Process Control Charts and the Problem of Interpretation: A Short Overview and Some Applications in Industry

  سند علمی۲۰۰۵S. Bersimis, J. Panaretos, S. Psarakis

  Woodall and Montgomery [35] in a discussion paper, state that multivariate process control is one of the most rapidly developing sections of statistical process control. Nowadays, in industry, there are many situations in which the simultaneous monitoring or control, of two or mo

• Multivariate Statistical Process Control Using LASSO

  سند علمی۲۰۰۹Changliang Zou, Peihua Qiu

  This paper develops a new multivariate statistical process control (SPC) methodology based on adapting the LASSO variable selection method to the SPC problem. The LASSO method has the sparsity property that it can select exactly the set of nonzero regression coefficients in multi

• On Reducing False Alarms in Multivariate Statistical Process Control

  سند علمی۲۰۰۹Tao Chen

  The primary objective of this note is to reduce the false alarms in multivariate statistical process control (MSPC). The issue of false alarms is inherent within MSPC as a result of the definition of control limits. It has been observed that under normal operating conditions, the

• Benefit Analysis of Process Oriented Basis Representation as a Method of Multivariate Statistical Process Control

  سند علمی۲۰۰۲Amanda Schmitt, Inge Marcus, Russell Barton

  Process-Oriented Basis Representation (POBREP) is an effective method of multivariate statistical process control that is seldom used in manufacturing. Rather than monitoring individual process variables, POBREP seeks to identify specific causes of production problems and map tho

• Epileptic Seizure Monitoring by Using Multivariate Statistical Process Control

  سند علمی۲۰۱۳Hirotsugu Hashimoto, Koichi Fujiwara, Yoko Suzuki, Miho Miyajima

  Although refractory epileptic patients suffer from uncontrolled seizures, their quality of life (QoL) may be improved if the seizure can be predicted in advance. In the preictal period, the excessive neuronal activity of epilepsy affects the autonomic nervous system. Since the fl

• Recent Advances in Multivariate Statistical Process Control: Improving Robustness and Sensitivity

  سند علمی۱۹۹۱B. M. Wise, N. L. Ricker

  Several extensions are made to the theory of multivariate process monitoring via Principal Components Analysis (PCA). An important robustness issue is addressed: the continued use of the PCA model after detection of a sensor failure. Without some adjustment, a single failed senso